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We consider {0, 1}n as a sample space with a probability measure on it, thus making pseudo-Boolean functions into random variables. We then derive explicit formulas for approximat...
Guoli Ding, Robert F. Lax, Jianhua Chen, Peter P. ...
We study the problem of approximating pseudoBoolean functions by linear pseudo-Boolean functions. Pseudo-Boolean functions generalize ordinary Boolean functions by allowing the fu...
Guoli Ding, Robert F. Lax, Peter P. Chen, Jianhua ...
We present a deterministic approximation algorithm to compute logarithm of the number of `good' truth assignments for a random k-satisfiability (k-SAT) formula in polynomial ...
Abstract— In [1], we have recently proposed a general approach for approximating the power sum of Log–Normal Random Variables (RVs) by using the Pearson system of distributions...
Marco Di Renzo, Fabio Graziosi, Fortunato Santucci
We study the intrinsic difficulty of solving linear parabolic initial value problems numerically at a single point. We present a worst case analysis for deterministic as well as fo...